AI Integration
AI integration services, on infrastructure you own
The hard part was never the model. It is choosing between forty vendors who all demo well, and then making the thing hold together against systems that were built before any of them existed.
AI integration is the work of connecting AI to the systems a business already runs — CRM, ERP, phone, ticketing, document stores — so the output arrives where people already work instead of in a separate chat window. Leverage Automated designs and builds those integrations on infrastructure the client owns, using whichever vendors fit the problem. We do not resell platforms and we do not host your data. If you are looking for a packaged product to buy off the shelf, we are the wrong firm.
Reviewed by Mat Wolfley, founder, Leverage Automated.
The actual problem
Nobody knows what to pick, and everybody offering to help sells one of the options
Ask five vendors how to add AI to your operation and you will get five architectures, each of which happens to require that vendor. That is not dishonesty exactly — it is what happens when the only people who understand the landscape are also selling inside it.
So the job we actually do is two things. First, help you choose: which model, which platform, which of this runs in your tenant, which of it should not be built at all. Second, make the choice hold together against the systems you already have, the ones with a decade of exceptions in them.
We are not selling a platform. We are selling the judgement about what to pick and the work to make it hold — on infrastructure that belongs to you.
What is in scope
- Vendor and model selection, including the case against the losers
- Integration into CRM, ERP, ticketing, telephony and document stores
- Data readiness and cleanup, which is where most of this fails
- Legacy system integration, including things without a modern API
- Voice agents, when a phone call is genuinely the right surface
Common triggers
- A proof of concept worked and nothing has moved since
- Staff are pasting company data into consumer chatbots
- Two departments bought overlapping tools that do not talk
- A vendor quoted an integration and the number seemed invented
- The data turned out to be in worse shape than anyone admitted
What you get
- A written recommendation with the rejected options and why
- Working integrations in your environment, not a slide deck
- Accounts and infrastructure in your name from day one
- A named senior engineer who does not rotate off mid-build
- An honest estimate of what it will cost you to run monthly
Examples
Examples of AI integration
AI integration is rarely one thing. In practice it means connecting a model to a system that already holds the work — the CRM, the ticket queue, the phone system, the document store — so the output lands where somebody is already looking instead of in a separate chat window. These are the shapes the work usually takes.
Every one of them runs on accounts held in the client’s own name. Leverage Automated builds and operates the integration; the platforms underneath it are bought directly from their vendors, the same way a server licence would be.
Where the work already lives
- Reading an inbound email, classifying it, and drafting the reply into the CRM record it belongs to
- Summarising a support thread into the ticket so the next person does not re-read forty messages
- Turning a phone call into a structured record with the follow-up already attached
Where the data already sits
- Answering staff questions from the document store, with the source named rather than paraphrased
- Pulling a figure out of a supplier PDF and putting it into the system that needs it
- Reconciling two systems that disagree, and escalating the ones a human should decide
Where the process already breaks
- Routing an exception to the right person instead of the default queue
- Catching the request that arrives outside the process entirely, by text or by voicemail
- Handing a task back to a human at the point the model should stop, and recording why
Ownership
The solution lives with you. We just help you build it
Every integration we work on belongs to the client. You open the accounts, you hold the contracts, the systems run in your environment. Client data does not rest on Leverage systems.
We take no margin on licences, seats, or model usage — those costs go straight to you at what the vendor actually charges. That is the thing that makes the recommendation trustworthy: we do not resell anything, which is exactly why we can tell you the honest answer about what to buy.
It also means there is nothing to be locked into. If you end the engagement the systems keep running, because they were never ours to switch off.
How we work
A demo has one path. Production has every path
Most AI projects die between the demo and the third week of real use, and it is almost never the model that kills them. It is the record that does not match, the department nobody consulted, the exception the process has quietly relied on for nine years, and the question of who gets paged when it breaks on a Friday.
So the engineering standards are unremarkable on purpose: staged rollout, a way back, logging you can read, and a person who owns it when it misbehaves. The AI is new. The operational discipline behind it is not, and that is deliberate.
Further reading
What we have written about this
The first decision is usually whether to build at all. Custom AI or off the shelf? walks the spectrum between the two and the four questions that settle most cases — including the change most people have not caught up with, which is that “custom” almost never means training a model any more.
If the answer is build, what drives the cost of an AI agent sets out what the number is actually made of, and why two quotes can differ by a factor of five while both being honest. Data cleansing before an AI project covers the part that is most often misjudged by both sides, in the order that matters.
On the engineering itself: what API integration costs you after it ships is the half of the bill that arrives after sign-off, and legacy modernization without a rewrite is for when one end of the integration is the system nobody wants to touch.
And on the risk of the easy path: somebody at your company may have put an AI agent on the public internet — a short self-audit you can run yourself, prompted by a July study of internet-facing MCP servers.
When the dependency itself degrades: seven major AI incidents in nine days — nine days of vendor status pages, counted, and why the fix is a route you build before you need it rather than a better choice of model.
Who you are actually talking to
I would rather tell you not to build it
Thirty years in IT, fifteen as a vCIO, and now hands-on with these systems every week. That last part matters more than the first two right now, because this field invalidates its own best practice about every quarter and a résumé cannot show you currency.
The most useful thing I do on a lot of these calls is talk somebody out of a project. Not as a negotiating posture — because a bad AI integration is worse than none. It costs money, it burns the organisation's patience for the next attempt, and the next attempt is usually the one that would have worked.
— Mat Wolfley, founder, Leverage Automated
This is probably not for you if
- —You want to buy a finished product. We build and integrate; we do not have a box to sell you.
- —You want us to host it and own the accounts. We deliberately do not — that is the point.
- —The data is off limits. If nobody can show us what condition it is in, an estimate would be fiction.
- —You need it live in two weeks because of an announcement. That is how pilots become wreckage.
If any of those describe you, say so on the first call and we will save each other the trouble.
The questions that actually get asked
How is this different from just using ChatGPT?
ChatGPT is a place a person goes. An integration is the AI arriving where the work already happens — the ticket, the record, the phone call, the inbox — without anyone copying anything between systems. The difference matters most for the things you cannot do in a chat window: acting on your live data, following your rules about who may see what, and leaving an audit trail. It also stops staff pasting company data into consumer accounts, which is usually already happening by the time anyone asks us.
Which AI vendor do you recommend?
It depends on the problem, and anyone who answers that question before seeing your systems is telling you about their business model rather than yours. We have no reseller agreements and take no margin on any platform, so the recommendation is not load-bearing for our revenue. What we will always give you is the shortlist, the rejected options, and the reason each one lost.
Do you host it, or do we?
You do. The accounts are opened in your name, the infrastructure is yours, and client data does not rest on Leverage systems. Plenty of firms prefer to host it for you because it creates recurring revenue and a switching cost. We would rather be kept because the work is good.
What does an AI integration cost?
We scope before quoting, and we do not publish a rate card. The number is driven by how many systems are touched, what condition the data is in, how many people have to agree on a change, and whether anything is load-bearing on day one. We also tell you the ongoing vendor cost separately and honestly, because that is the figure that surprises people six months in — and it is a cost you pay the vendor directly, not us.
Our data is a mess. Is that a problem?
It is the normal starting condition, and it is the single best predictor of whether an AI project works. Most failed AI projects were data projects that nobody scoped as one. We would rather find that in week one and tell you than discover it in month four. Sometimes the honest recommendation is to fix the data and revisit AI afterwards.
Can you integrate with an old system that has no API?
Often, yes — that is a large part of what integration work actually is. Legacy systems are usually reachable by some route: a database, a file drop, a scheduled export, a middleware layer, occasionally something less elegant. What we will tell you honestly is when the route is fragile enough that you should not build anything load-bearing on top of it.
Who owns the code you write?
You do. It runs in your environment, in accounts you hold, and you keep it if the engagement ends. We are not building a platform you rent back from us.
Can we just ask you a question first?
Please do. If you have been asked to come back with an answer about AI and you want one thing checked before a meeting, email or call. No form gate and no obligation to become a client — being useful before there is a contract is most of how this works.
Ask us before you have to answer
Tell us what you already run and what you have been asked to fix. If the honest answer is that you should not build it, we will say that first.
Seattle, WA — working nationwide.